Whole-genome sequencing as an investigational device for return of hereditary disease risk and pharmacogenomic results as part of the All of Us Research Program.

BACKGROUND: The All of Us Research Program (AoURP, "the program") is an initiative, sponsored by the National Institutes of Health (NIH), that aims to enroll one million people (or more) across the USA. Through repeated engagement of participants, a research resource is being created to enable a variety of future observational and interventional studies. The program has also committed to genomic data generation and returning important health-related information to participants. METHODS: Whole-genome sequencing (WGS), variant calling processes, data interpretation, and return-of-results procedures had to be created and receive an Investigational Device Exemption (IDE) from the United States Food and Drug Administration (FDA). The performance of the entire workflow was assessed through the largest known cross-center, WGS-based, validation activity that was refined iteratively through interactions with the FDA over many months. RESULTS: The accuracy and precision of the WGS process as a device for the return of certain health-related genomic results was determined to be sufficient, and an IDE was granted. CONCLUSIONS: We present here both the process of navigating the IDE application process with the FDA and the results of the validation study as a guide to future projects which may need to follow a similar path. Changes to the program in the future will be covered in supplementary submissions to the IDE and will support additional variant classes, sample types, and any expansion to the reportable regions.

Predominance of antibody-resistant SARS-CoV-2 variants in vaccine breakthrough cases from the San Francisco Bay Area, California.

Associations between vaccine breakthrough cases and infection by different SARS coronavirus 2 (SARS-CoV-2) variants have remained largely unexplored. Here we analysed SARS-CoV-2 whole-genome sequences and viral loads from 1,373 persons with COVID-19 from the San Francisco Bay Area from 1 February to 30 June 2021, of which 125 (9.1%) were vaccine breakthrough infections. Vaccine breakthrough infections were more commonly associated with circulating antibody-resistant variants carrying ≥1 mutation associated with decreased antibody neutralization (L452R/Q, E484K/Q and/or F490S) than infections in unvaccinated individuals (78% versus 48%, P = 1.96 × 10-8). Differences in viral loads were non-significant between unvaccinated and fully vaccinated cases overall (P = 0.99) and according to lineage (P = 0.09-0.78). Symptomatic vaccine breakthrough infections had comparable viral loads (P = 0.64), whereas asymptomatic breakthrough infections had decreased viral loads (P = 0.023) compared with infections in unvaccinated individuals. In 5 cases with serial samples available for serologic analyses, vaccine breakthrough infections were found to be associated with low or undetectable neutralizing antibody levels attributable to an immunocompromised state or infection by an antibody-resistant lineage. Taken together, our results show that vaccine breakthrough infections are overrepresented by antibody-resistant SARS-CoV-2 variants, and that symptomatic breakthrough infections may be as efficient in spreading COVID-19 as unvaccinated infections, regardless of the infecting lineage.

Intronic Breakpoint Signatures Enhance Detection and Characterization of Clinically Relevant Germline Structural Variants.

The relevance of large copy number variants (CNVs) to hereditary disorders has been long recognized, and population sequencing efforts have chronicled many common structural variants (SVs). However, limited data are available on the clinical contribution of rare germline SVs. Here, a detailed characterization of SVs identified using targeted next-generation sequencing was performed. Across 50 genes associated with hereditary cancer and cardiovascular disorders, a minimum of 828 unique SVs were reported, including 584 fully characterized SVs. Almost 40% of CNVs were <5 kb, with one in three deletions impacting a single exon. Additionally, 36 mid-range deletions/duplications (50 to 250 bp), 21 mobile element insertions, 6 inversions, and 27 complex rearrangements were detected. This data set was used to model SV detection in a bioinformatics pipeline solely relying on read depth, which revealed that genome sequencing (30×) allows detection of 71%, a 500× panel only targeting coding regions 53%, and exome sequencing (100×) <20% of characterized SVs. SVs accounted for 14.1% of all unique pathogenic variants, supporting the importance of SVs in hereditary disorders. Robust SV detection requires an ensemble of variant-calling algorithms that utilize sequencing of intronic regions. These algorithms should use distinct data features representative of each class of mutational mechanism, including recombination between two sequences sharing high similarity, covariants inserted between CNV breakpoints, and complex rearrangements containing inverted sequences.

LEAP: Using machine learning to support variant classification in a clinical setting.

Advances in genome sequencing have led to a tremendous increase in the discovery of novel missense variants, but evidence for determining clinical significance can be limited or conflicting. Here, we present Learning from Evidence to Assess Pathogenicity (LEAP), a machine learning model that utilizes a variety of feature categories to classify variants, and achieves high performance in multiple genes and different health conditions. Feature categories include functional predictions, splice predictions, population frequencies, conservation scores, protein domain data, and clinical observation data such as personal and family history and covariant information. L2-regularized logistic regression and random forest classification models were trained on missense variants detected and classified during the course of routine clinical testing at Color Genomics (14,226 variants from 24 cancer-related genes and 5,398 variants from 30 cardiovascular-related genes). Using 10-fold cross-validated predictions, the logistic regression model achieved an area under the receiver operating characteristic curve (AUROC) of 97.8% (cancer) and 98.8% (cardiovascular), while the random forest model achieved 98.3% (cancer) and 98.6% (cardiovascular). We demonstrate generalizability to different genes by validating predictions on genes withheld from training (96.8% AUROC). High accuracy and broad applicability make LEAP effective in the clinical setting as a high-throughput quality control layer.

Correction: Sherloc: a comprehensive refinement of the ACMG-AMP variant classification criteria.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Assessment of blind predictions of the clinical significance of BRCA1 and BRCA2 variants.

Testing for variation in BRCA1 and BRCA2 (commonly referred to as BRCA1/2), has emerged as a standard clinical practice and is helping countless women better understand and manage their heritable risk of breast and ovarian cancer. Yet the increased rate of BRCA1/2 testing has led to an increasing number of Variants of Uncertain Significance (VUS), and the rate of VUS discovery currently outpaces the rate of clinical variant interpretation. Computational prediction is a key component of the variant interpretation pipeline. In the CAGI5 ENIGMA Challenge, six prediction teams submitted predictions on 326 newly-interpreted variants from the ENIGMA Consortium. By evaluating these predictions against the new interpretations, we have gained a number of insights on the state of the art of variant prediction and specific steps to further advance this state of the art.

Multi-Gene Panel Testing of 23,179 Individuals for Hereditary Cancer Risk Identifies Pathogenic Variant Carriers Missed by Current Genetic Testing Guidelines.

Recent advancements in next-generation sequencing have greatly expanded the use of multi-gene panel testing for hereditary cancer risk. Although genetic testing helps guide clinical diagnosis and management, testing recommendations are based on personal and family history of cancer and ethnicity, and many carriers are being missed. Herein, we report the results from 23,179 individuals who were referred for 30-gene next-generation sequencing panel testing for hereditary cancer risk, independent of current testing guidelines-38.7% of individuals would not have met National Comprehensive Cancer Network criteria for genetic testing. We identified a total of 2811 pathogenic variants in 2698 individuals for an overall pathogenic frequency of 11.6% (9.1%, excluding common low-penetrance alleles). Among individuals of Ashkenazi Jewish descent, three-quarters of pathogenic variants were outside of the three common BRCA1 and BRCA2 founder alleles. Across all ethnic groups, pathogenic variants in BRCA1 and BRCA2 occurred most frequently, but the contribution of pathogenic variants in other genes on the panel varied. Finally, we found that 21.7% of individuals with pathogenic variants in genes with well-established genetic testing recommendations did not meet corresponding National Comprehensive Cancer Network criteria. Taken together, the results indicate that more individuals are at genetic risk for hereditary cancer than are identified by current testing guidelines and/or use of single-gene or single-site testing.

Scaling resolution of variant classification differences in ClinVar between 41 clinical laboratories through an outlier approach.

ClinVar provides open access to variant classifications shared from many clinical laboratories. Although most classifications are consistent across laboratories, classification differences exist. To facilitate resolution of classification differences on a large scale, clinical laboratories were encouraged to reassess outlier classifications of variants with medically significant differences (MSDs). Outliers were identified by first comparing ClinVar submissions from 41 clinical laboratories to detect variants with MSDs between the laboratories (650 variants). Next, MSDs were filtered for variants with ≥3 classifications (244 variants), of which 87.6% (213 variants) had a majority consensus in ClinVar, thus allowing for identification of outlier classifications in need of reassessment. Laboratories with outlier classifications were sent a custom report and encouraged to reassess variants. Results were returned for 204 (96%) variants, of which 62.3% (127) were resolved. Of those 127, 64.6% (82) were resolved due to reassessment prompted by this study and 35.4% (45) resolved by a previously completed reassessment. This study demonstrates a scalable approach to classification resolution and capitalizes on the value of data sharing within ClinVar. These activities will help the community move toward more consistent variant classifications, which will improve the care of patients with, or at risk for, genetic disorders.

Corrigendum: Sources of discordance among germ-line variant classifications in ClinVar.

This corrects the article DOI: 10.1038/gim.2017.60.

Consistency of BRCA1 and BRCA2 Variant Classifications Among Clinical Diagnostic Laboratories.

BACKGROUND: Genetic tests of the cancer predisposition genes BRCA1 and BRCA2 inform significant clinical decisions for both physicians and patients. Most uncovered variants are benign, and determining which few are pathogenic (disease-causing) is sometimes challenging and can potentially be inconsistent among laboratories. The ClinVar database makes de-identified clinical variant classifications from multiple laboratories publicly available for comparison and review, per recommendations of the American Medical Association (AMA), the American College of Medical Genetics (ACMG), the National Society for Genetic Counselors (NSGC), and other organizations. METHODS: Classifications of more than 2000 BRCA1/2 variants in ClinVar representing approximately 22,000 patients were dichotomized as clinically actionable or not actionable and compared across up to seven laboratories. The properties of these variants and classification differences were investigated in detail. RESULTS: Per-variant concordance was 98.5% (CI 97.9%-99.0%). All discordant variants were rare; thus, per patient concordance was estimated to be higher: 99.7%. ClinVar facilitated resolution of many of the discordant variants, and concordance increased to 99.0% per variant and 99.8% per patient when reclassified (but not yet resubmitted) variants and submission errors were addressed. Most of the remaining discordances appeared to involve either legitimate differences in expert judgment regarding particular scientific evidence, or were classifications that predated availability of important scientific evidence. CONCLUSIONS: Significant classification disagreements among the professional clinical laboratories represented in ClinVar are infrequent yet important. The unrestricted sharing of clinical genetic data allows detailed interlaboratory quality control and peer review, as exemplified by this study.

Sources of discordance among germ-line variant classifications in ClinVar.

PurposeClinVar is increasingly used as a resource for both genetic variant interpretation and clinical practice. However, controversies exist regarding the consistency of classifications in ClinVar, and questions remain about how best to use these data. Our study systematically examined ClinVar to identify common sources of discordance and thus inform ongoing practices.MethodsWe analyzed variants that had multiple classifications in ClinVar, excluding benign polymorphisms. Classifications were categorized by potential actionability and pathogenicity. Consensus interpretations were calculated for each variant, and the properties of the discordant outlier classifications were summarized.ResultsOur study included 74,065 classifications of 27,224 unique variants in 1,713 genes. We found that (i) concordance rates differed among clinical areas and variant types; (ii) clinical testing methods had much higher concordance than basic literature curation and research efforts; (iii) older classifications had greater discordance than newer ones; and (iv) low-penetrance variants had particularly high discordance.ConclusionRecent variant classifications from clinical testing laboratories have high overall concordance in many (but not all) clinical areas. ClinVar can be a reliable resource supporting variant interpretation, quality assessment, and clinical practice when factors uncovered in this study are taken into account. Ongoing improvements to ClinVar may make it easier to use, particularly for nonexpert users.

Sherloc: a comprehensive refinement of the ACMG-AMP variant classification criteria.

PurposeThe 2015 American College of Medical Genetics and Genomics-Association for Molecular Pathology (ACMG-AMP) guidelines were a major step toward establishing a common framework for variant classification. In practice, however, several aspects of the guidelines lack specificity, are subject to varied interpretations, or fail to capture relevant aspects of clinical molecular genetics. A simple implementation of the guidelines in their current form is insufficient for consistent and comprehensive variant classification.MethodsWe undertook an iterative process of refining the ACMG-AMP guidelines. We used the guidelines to classify more than 40,000 clinically observed variants, assessed the outcome, and refined the classification criteria to capture exceptions and edge cases. During this process, the criteria evolved through eight major and minor revisions.ResultsOur implementation: (i) separated ambiguous ACMG-AMP criteria into a set of discrete but related rules with refined weights; (ii) grouped certain criteria to protect against the overcounting of conceptually related evidence; and (iii) replaced the "clinical criteria" style of the guidelines with additive, semiquantitative criteria.ConclusionSherloc builds on the strong framework of 33 rules established by the ACMG-AMP guidelines and introduces 108 detailed refinements, which support a more consistent and transparent approach to variant classification.

Pathogenic variant burden in the ExAC database: an empirical approach to evaluating population data for clinical variant interpretation.

BACKGROUND: The frequency of a variant in the general population is a key criterion used in the clinical interpretation of sequence variants. With certain exceptions, such as founder mutations, the rarity of a variant is a prerequisite for pathogenicity. However, defining the threshold at which a variant should be considered "too common" is challenging and therefore diagnostic laboratories have typically set conservative allele frequency thresholds. METHODS: Recent publications of large population sequencing data, such as the Exome Aggregation Consortium (ExAC) database, provide an opportunity to characterize with accuracy and precision the frequency distributions of very rare disease-causing alleles. Allele frequencies of pathogenic variants in ClinVar, as well as variants expected to be pathogenic through the nonsense-mediated decay (NMD) pathway, were analyzed to study the burden of pathogenic variants in 79 genes of clinical importance. RESULTS: Of 1364 BRCA1 and BRCA2 variants that are well characterized as pathogenic or that are expected to lead to NMD, 1350 variants had an allele frequency of less than 0.0025%. The remaining 14 variants were previously published founder mutations. Importantly, we observed no difference in the distributions of pathogenic variants expected to be lead to NMD compared to those that are not. Therefore, we expanded the analysis to examine the distributions of NMD expected variants in 77 additional genes. These 77 genes were selected to represent a broad set of clinical areas, modes of inheritance, and penetrance. Among these variants, most (97.3%) had an allele frequency of less than 0.01%. Furthermore, pathogenic variants with allele frequencies greater than 0.01% were well characterized in publications and included many founder mutations. CONCLUSIONS: The observations made in this study suggest that, with certain caveats, a very low allele frequency threshold can be adopted to more accurately interpret sequence variants.

Clinical Genetic Testing for the Cardiomyopathies and Arrhythmias: A Systematic Framework for Establishing Clinical Validity and Addressing Genotypic and Phenotypic Heterogeneity.

Advances in DNA sequencing have made large, diagnostic gene panels affordable and efficient. Broad adoption of such panels has begun to deliver on the promises of personalized medicine, but has also brought new challenges such as the presence of unexpected results, or results of uncertain clinical significance. Genetic analysis of inherited cardiac conditions is particularly challenging due to the extensive genetic heterogeneity underlying cardiac phenotypes, and the overlapping, variable, and incompletely penetrant nature of their clinical presentations. The design of effective diagnostic tests and the effective use of the results depend on a clear understanding of the relationship between each gene and each considered condition. To address these issues, we developed simple, systematic approaches to three fundamental challenges: (1) evaluating the strength of the evidence suggesting that a particular condition is caused by pathogenic variants in a particular gene, (2) evaluating whether unusual genotype/phenotype observations represent a plausible expansion of clinical phenotype associated with a gene, and (3) establishing a molecular diagnostic strategy to capture overlapping clinical presentations. These approaches focus on the systematic evaluation of the pathogenicity of variants identified in clinically affected individuals, and the natural history of disease in those individuals. Here, we applied these approaches to the evaluation of more than 100 genes reported to be associated with inherited cardiomyopathies and arrhythmias including hypertrophic cardiomyopathy, dilated cardiomyopathy, arrhythmogenic right ventricular dysplasia or cardiomyopathy, long QT syndrome, short QT syndrome, Brugada, and catecholaminergic polymorphic ventricular tachycardia, and to a set of related syndromes such as Noonan Syndrome and Fabry disease. These approaches provide a framework for delivering meaningful and accurate genetic test results to individuals with hereditary cardiac conditions.

Reinitiation of mRNA translation in a patient with X-linked infantile spasms with a protein-truncating variant in ARX.

Mutations in the Aristaless-related homeobox gene (ARX) lead to a range of X-linked intellectual disability phenotypes, with truncating variants generally resulting in severe X-linked lissencephaly with ambiguous genitalia (XLAG), and polyalanine expansions and missense variants resulting in infantile spasms. We report two male patients with early-onset infantile spasms in whom a novel c.34G>T (p.(E12*)) variant was identified in the ARX gene. A similar variant c.81C>G (p.(Y27*)), has previously been described in two affected cousins with early-onset infantile spasms, leading to reinitiation of ARX mRNA translation resulting in an N-terminal truncated protein. We show that the novel c.34G>T (p.(E12*)) variant also reinitiated mRNA translation at the next AUG codon (c.121-123 (p.M41)), producing the same N-terminally truncated protein. The production of both of these truncated proteins was demonstrated to be at markedly reduced levels using in vitro cell assays. Using luciferase reporter assays, we demonstrate that transcriptional repression capacity of ARX was diminished by both the loss of the N-terminal corepressor octapeptide domain, as a consequence of truncation, and the marked reduction in mutant protein expression. Our study indicates that premature termination mutations very early in ARX lead to reinitiation of translation to produce N-terminally truncated protein at markedly reduced levels of expression. We conclude that even low levels of N-terminally truncated ARX is sufficient to improve the patient's phenotype compared with the severe phenotype of XLAG that includes malformations of the brain and genitalia normally seen in complete loss-of-function mutations in ARX.

Loss-of-function alanyl-tRNA synthetase mutations cause an autosomal-recessive early-onset epileptic encephalopathy with persistent myelination defect.

Mutations in genes encoding aminoacyl-tRNA synthetases are known to cause leukodystrophies and genetic leukoencephalopathies-heritable disorders that result in white matter abnormalities in the central nervous system. Here we report three individuals (two siblings and an unrelated individual) with severe infantile epileptic encephalopathy, clubfoot, absent deep tendon reflexes, extrapyramidal symptoms, and persistently deficient myelination on MRI. Analysis by whole exome sequencing identified mutations in the nuclear-encoded alanyl-tRNA synthetase (AARS) in these two unrelated families: the two affected siblings are compound heterozygous for p.Lys81Thr and p.Arg751Gly AARS, and the single affected child is homozygous for p.Arg751Gly AARS. The two identified mutations were found to result in a significant reduction in function. Mutations in AARS were previously associated with an autosomal-dominant inherited form of axonal neuropathy, Charcot-Marie-Tooth disease type 2N (CMT2N). The autosomal-recessive AARS mutations identified in the individuals described here, however, cause a severe infantile epileptic encephalopathy with a central myelin defect and peripheral neuropathy, demonstrating that defects of alanyl-tRNA charging can result in a wide spectrum of disease manifestations.

The first case of CDK5RAP2-related primary microcephaly in a non-consanguineous patient identified by next generation sequencing.

Primary autosomal recessive microcephaly (MCPH) is a genetically heterogeneous condition characterized by congenital microcephaly and intellectual disability. To date, 10 MCPH loci have been identified and due to the genetic heterogeneity of this condition, molecular testing for MCPH can be complicated. Our methods involved employing a next generation sequencing panel of MCPH-related genes allowing for the evaluation of multiple disease loci simultaneously. Next generation sequencing analysis of a 6 year old female with primary microcephaly identified novel compound heterozygous mutations (c.524_528del and c.4005-1G>A) in the CDK5RAP2 gene. A review of the published literature to date reveals that only three mutations have been previously reported in the CDK5RAP2 gene in the homozygous state in three Northern Pakistani and one Somali consanguineous MCPH families. Our patient represents the first non-consanguineous Caucasian individual to have been identified with CDK5RAP2-related MCPH. As only a handful of patients have been reported in the literature with CDK5RAP2-related MCPH, we anticipate the identification of individuals with CDK5RAP2 mutations from all ethnic backgrounds will continue. Our patient contributes to the ethnic and genotypic spectrum of CDK5RAP2-related MCPH and supports the occurrence of this genetic condition beyond that of consanguineous families of certain ethnic populations. Our results also highlight the utility of multi-gene sequencing panels to elucidate the etiology of genetically heterogeneous conditions.